TRLUP– Zester

Many Canadian companies and researchers struggle to find affordable, secure, and easy-to-use data labelling tools. Most existing platforms are foreign-owned, which can cause privacy issues and make it harder for small teams to work with sensitive information. It also prevents us from building local expertise and jobs in AI data management. Zester aims to solve this by developing a secure and scalable data labelling platform built entirely in Canada. The first version will focus on agricultural data because Saskatchewan has a strong base in agri-tech and applied research. The Minimum Viable Product (MVP) will support both manual and AI-assisted labelling, and it will be built in a way that can later support a no-code automation feature so users can design their own workflows easily. For Saskatchewan Polytechnic, this project creates a bridge between classroom knowledge and real-world software development challenges. For North Forge, it shows how a locally built data tool can grow into a larger startup opportunity. By the end of the internship, the project will deliver a functional MVP, a detailed technical and business report, and a go-to-market strategy. This project helps Canada strengthen its AI infrastructure while keeping data safe and jobs local.

Faculty Supervisor:

Terry Peckham

Student:

Partner:

North Forge

Discipline:

Computer science

Sector:

Education; Management of companies and enterprises; Professional, scientific and technical services

University:

Saskatchewan Polytechnic

Program: